US8498465B2ActiveUtilityA1
Accurate determination of the shape and localization of metallic object(s) in X-ray CT imaging
Est. expirySep 29, 2029(~3.2 yrs left)· nominal 20-yr term from priority
G06T 12/10G06T 2207/30052G06T 7/149G06T 7/12G06T 2207/10081
61
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Claims
Abstract
A binary image reconstruction method is provided to identify metal objects in a computer tomography (CT) image. The method includes providing a suitably programmed computer, providing a CT image, where the CT image includes intensity data, and the suitably programmed computer is used to determine a first range of attenuation coefficient values and a second range of attenuation coefficient values in the intensity data, where when a difference between the first range of attenuation coefficient values and the second range of attenuation coefficient values is less than a pre-determined gradient threshold value, a boundary of a metal object in the CT image is determined.
Claims
exact text as granted — not AI-modifiedWhat is claimed:
1. A binary image reconstruction method to identify metal objects in a computer tomography (CT) image, comprising:
a. providing a suitably programmed computer;
b. providing a CT image, wherein said CT image comprises intensity data, wherein said suitably programmed computer is used to determine a first range of attenuation coefficient values and a second range of attenuation coefficient values in said intensity data, wherein when a difference between said first range of attenuation coefficient values and said second range of attenuation coefficient values is less than a pre-determined gradient threshold value a boundary of a metal object in said CT image is determined.
2. The binary image reconstruction method of claim 1 , wherein said determination of said attenuation coefficient ranges comprises applying a penalized weighted least squares (PLWS) criterion to minimize an objective function, wherein said objective function comprises a data fidelity term and a regularization term, wherein said regularization term characterizes an a priori attenuation coefficient of said intensity data.
3. The binary image reconstruction method of claim 2 , wherein said regularization term is only applied for adjacent data elements having a gradient value smaller than a predetermined threshold value, wherein when said regularization term is applied to said CT image comprising metal object data or tissue data a reconstructed output image shows only a metal object and a masked patient structure background.
4. The binary image reconstruction method of claim 1 , wherein said first range of attenuation coefficient values is assigned a value of 0 and said second range of attenuation coefficient values is assigned a value of 1, wherein a region in said CT image where said attenuation coefficient values change from 0 to 1 comprises a boundary of a metal object in said CT image.Cited by (0)
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